The present invention relates to metrology for semiconductor manufacturing a applications, and in particular to a method and system for reducing measurement inaccuracies.
As integrated circuits evolve towards smaller critical dimensions (CD""s) and faster response time, new challenges are encountered in the manufacturing processes. Accurate metrology for measurement of features with sizes on the order of 100 nm or smaller is desirable.
Optical metrology has emerged as an effective tool, with several advantages over other metrology methods such as Scanning Electron Microscopy (SEM). Optical probes are non-destructive, can be employed in production monitoring and control, and can be used for determination of thickness and topographic information as well as for CD measurement.
In a method for optical metrology known as Optical Digital Profilometry (ODP), scatterometry is used to reconstruct a diffraction grating profile from its optical diffraction responses, at a fixed incident angle and multiple wavelengths. A library-based methodology for profile extraction is provided, whereby libraries of spectral responses are created for simulated grating profiles which include such detailed profile characteristics as: rounding, footing, T-topping, material thickness variation, sidewall angles, and CD variation. Mask information, thin-film information such as parameters describing optical properties n and k, and thickness values, are inputs that are used to compute the diffraction signal, which may be a spectral scattering response signal, of a collection of simulated profiles. To determine the profile of a sample, e.g. an integrated circuit, having periodic structures, the spectral scattering response is measured for that sample. The measured spectral scattering response from the sample is compared with the library of simulated spectral scattering responses, and a best match is found, i.e., a profile whose simulated diffraction signals best match the actual measured diffraction signals.
The simulated spectral scattering responses are typically calculated by a grating response simulator which utilizes Rigorous Coupled-Wave Analysis (RCWA) analytical techniques, as described in the article by Niu et al. Other simulation algorithms may also be used to calculate the spectral scattering responses. An integral method is described in xe2x80x9cNumerical Methods for the Analysis of Scattering from Nonplanar Periodic Structures,xe2x80x9d, A. R. Neureuther and K Zaki, Int""l URSI Symposium on Electromagnetic Waves, Stresa, Italy, pp 282-285, 1969. A differential method is described in xe2x80x9cSystematic Study of Resonances Holographic Thin Film Coulersxe2x80x9d, M Neviere et al, Optics Communications, Vol. 9, No. 1, pp 48-53, September 1973.
The hardware used in conjunction with metrology, which may include a metrology beam source, ellipsometer, and reflectometer, is subject to parameters that are not exactly reproducible. Examples of metrology hardware-related variable parameters include: angle of metrology beam incidence, numerical aperture, wavelength range, polarization, and noise. These metrology hardware parameters may display time variation (within a specification range) for a single piece of metrology hardware, and they may also vary between pieces of metrology hardware of the same type.
In addition to the variability of metrology hardware-related parameters, material-based parameters, e.g., optical characteristics n and k, may vary from sample batch to batch (as in different semiconductor wafer batches) or across a single batch of material (as in wafer-to-wafer variations).
The variation in metrology hardware and material parameters has caused problems relating to metrology. The user determined accuracy requirements from metrology systems are generally based on the measurement accuracy, e.g., accuracy of measured CD""s. However, the accuracy of metrology hardware is based on hardware specification ranges, i.e., the variability of hardware parameters. The relationship between the metrology hardware specification ranges and the associated measurement accuracy is not generally available for the hardware designer and the user.
A second problem occurs in library-based metrology systems. The library diffraction signals are calculated according to inputs based on a particular set of hardware specifications, and according to ideal material characteristics. If the actual pieces of hardware and batch of material used in the measurement of a sample""s diffraction signal have slightly different specifications or characteristics than those used in the library calculations, inaccuracies are incurred when matching the measured diffraction signal to the calculated library diffraction signals.
The method in accordance with embodiments of the present invention relates to a method and system for incorporating the effects of metrology hardware and material variations into a calculated diffraction signal library used in metrology, optical metrology being one example.
In a first embodiment, a method is disclosed for determining metrology hardware specification ranges that correspond to acceptable CD measurement accuracy. In this method, simulated diffraction spectra are calculated corresponding to varying metrology hardware parameters within hardware specification ranges. These spectra may be calculated using a grating response simulator. The correspondences between changes in metrology hardware parameters and changes in CD measurements are determined by comparisons with library spectra. Acceptable metrology hardware specification ranges are then linked to acceptable CD measurement accuracy. The correspondence may be utilized in two ways: either by specifying desired measurement accuracy and calculating necessary metrology hardware specification ranges to provide that accuracy, or by calculating measurement accuracy resulting from given metrology hardware specification ranges.
In a second embodiment, a method for modifying a library diffraction spectrum so as to be optimized to the particular parameters of a specific piece of metrology hardware and specific material batches is disclosed. A parameter modification vector, which describes the differences between the actual measurement parameters and the parameters used in calculating the library spectra, is determined from metrology hardware specifications and material properties for the particular system and material in use. This parameter modification vector is used to calculate the corresponding modification to the library diffraction spectrum. A modified library can then be created, which is used to more accurately profile samples using the specific material batch and the specific metrology hardware.